Calculate weighted average of a 2D matrix

Dear all, I hope all is well. I am working with a 2D Matrix that is 376x481. I would like to calculate the weighted average of this matrix for each row, such that the desired output should be sized 376 X 1. I would greatly appreciate any help with this problem.

Thanks.

Answer 1

[James Tursa]

E.g.,

w = 1x481 vector of weights
M = your 376x481 matrix of values
result = sum(M.*w,2) / sum(w);

or

sum(bsxfun(@times,M,w),2) / sum(w);

[Abdul Wahab]

Could you elaborate on how you are determining the weight vector? All I have for my data set is a 376 x 481 matrix

[James Tursa]

I am not determining the weights ... that is something that you would do for your specific problem. You stated that you wanted a weighted average, so I assumed you had some weights in mind. This would be something specific to your problem and is not something we can come up with for you. If you make all the weights the same you will just get the usual unweighted average (same thing you would get by using the mean() function directly).

[Abdul Wahab]

Thank you for your detailed answer. I am currently trying to figure out the weight vector of all the row elements in a 376 x 481 matrix. I guess I should have phrased the question differently. Is there a way to calculate the weight vector as such?

[James Tursa]

Can you provide us with some info on what data this matrix contains and how it was generated? Then maybe we can make a stab at what you might want to do for weights.

[Abdul Wahab]

This matrix is populated with a non-dimensional variable (376 rows) and associated time history of 481 hours. So each row is then a representation of how this non-dimensional variable is changing through 481 hours (one column for every hour). This non-dimensional number varies in a specific order where it contains both unique and non-unique values of this non-dimensional variable. I would like to figure out the weight vector of the non-unique and unique values in every row and get the weighted average instead of a simple mean. I hope this provides some more insight into my problem.

Answer 2

[Thorsten]

X = rand(376, 481);
w = rand(1, size(X, 2));
Xw = bsxfun(@times, X, w);
m = mean(Xw, 2);

[stelios loizidis]

Hello,

I saw the commands you wrote above and I have the following question; I have a matrix e.g

[ 5 3 3 1
  3 4 5 2
  5 0 0 0
  3 4 5 2 ]

For this matrix I have to make a weighted average for each row. That is [5+3+(4/5)*(3+1)] / 4 =16/5. Also, if there is only one number and the rest zero (row 3) the weighted average should be [5+0+0+0]/ 1 =5 and the end we choose the largest weight average. How does this work?